class_docstr: This class allows you to specify skipping a ``Seq2SeqEncoder`` just
  by changing a configuration file. This is useful for ablations and
  measuring the impact of different elements of your model.
code: def forward(
      self, inputs, mask=None  # pylint: disable=arguments-differ
  ):
      # pylint: disable=unused-argument
  
      return inputs
  
file_path: magnitude/pymagnitude/third_party/allennlp/modules/seq2seq_encoders/pass_through_encoder.py
imports: from __future__ import absolute_import
  import torch
  from allennlp.modules.seq2seq_encoders.seq2seq_encoder import Seq2SeqEncoder
label_desc: Use image node_id 5 for calling the PassThroughEncoder obj's underlying member method code with example usage: obj.forward(inputs, mask) and returns: inputs